Welo Global - Quality Analyst — Generative AI Data Quality
Requirements
• · Bachelor’s degree or equivalent experience in Business, Operations, Quality, or Data/Engineering. • · 2+ years in quality/ops with hands-on QA and workforce/training coordination. • · 1+ years leading people/pods (formal or informal). • · Multi-project planning and stakeholder management. • · Clear client communications and governance cadence participation. • · Strong spreadsheets, PM/task boards, and basic BI; ETL familiarity is a plus. • · Capacity planning with vendors; confident escalation/negotiation. • · Effective in global, distributed teams. • · Near-native English with strong writing and editorial skills. • · Hands-on with generative AI tools (text/voice/video). • · Background in QA testing, rubric design, or AI safety/ethics evaluation. • · Familiarity with data-annotation platforms and model-evaluation tools. • · Ability to interpret code/datasets/workflows at a conceptual level (no coding required). • · Works independently and manages workflows effectively in a remote setup. • · Multilingual ability beyond English. • Scope & Autonomy • · Leads quality, training, and performance tracks across several projects; independent within guardrails. • · Shared accountability for client results and team performance with Ops Manager. • Job Reference: #LI-JC1 • We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Responsibilities
• · Set client QA strategies (sampling design, audit methods, acceptance thresholds) and adapt to scope/volume changes. • · Run root-cause analyses; drive CAPA plans with owners, timelines, and effectiveness checks. • · Plan training & certification for raters/annotators and coordinators; track completion and impact. • · Maintain dashboards (throughput, accuracy, productivity, cost) and convert insights into actions. • · Manage client escalations; present options, trade-offs, and recovery paths. • · Standardize SOPs, templates, and checklists; remove bottlenecks. • · Pilot small automations (macros, templates, RPA/API handoffs) with Ops Tech; scale wins. • · Coach P1s and C2–C3 on tools, workflows, and QA craft. • · Ensure compliance/security across data handling and platform access.
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